CN103870552B - Scrambling and recovery method for GIS (Geographic Information System) vector data line and plane graphic layer - Google Patents

Abstract

The invention discloses a scrambling and recovery method for a GIS (Geographic Information System) vector data line and plane graphic layer and belongs to the field of geographic information security. The method is based on quasi-affine transformation in a finite integer field and mainly comprises the following processes: 1) a scrambling process, which comprises the steps of constructing a vector data finite field scrambling transformation space, determining transformation rules, generating transformation parameters, performing global scrambling, removing virtual points, forming scrambled vector data and the like; 2) a recovery process, which comprises the steps of generating inverse transformation parameters, performing global anti-scrambling, forming and displaying recovered vector data and the like. The method disclosed by the invention has the characteristics of randomness, reversibility and the like, the recovery transformation has a simple analytical expression, recovery can be realized without performing periodic iteration and effectively technical means are provided for safe transmission, packaging and storage of geographic spatial data.

Description

A method of scrambling and restoring GIS vector data line-surface layer

technical field

The invention belongs to the field of geographic information security, and specifically relates to a method for scrambling and restoring GIS vector data line-surface layers based on quasi-affine transformation on a finite integer field, which can realize safe transmission and access of vector data in the field of geographic information systems .

Background technique

GIS vector data has the incomparable advantages of traditional paper maps such as high precision, massive volume, easy storage, automatic processing, and lossless scaling, and has a wide range of applications. Tampering, therefore, the research on the security of GIS vector data is very important. The existing encryption methods are mainly aimed at the change of coordinate precision to achieve encryption, and most of the encryption granularity is relatively coarse, without considering the topological relationship between elements, so starting from the perspective of destroying the spatial relationship first, based on the point order The GIS vector data scrambling method is an important information encryption technology and an effective security enhancement method, which is of great significance for improving the security of network information transmission.

The principle of GIS vector data scrambling is to scramble the point number (x, y) to the point number (x′, y′), that is, assign the attribute value at the original point (x, y) to (x′, y′). Daubechies, I. (1996) expounded the idea of reversible transformation from integer to integer, and Zhu Guibin (2003) gave an image scrambling algorithm based on quasi-affine transformation.

Integer promotion transforms can implement reversible integer-to-integer transformations:

For affine transformations of the following special form:

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; \&alpha;</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

The corresponding integer transformation can be constructed as

in represents the integer part of x (symbol Indicates a rounding operation), add 0.5 for rounding. It can be seen from the formula (2) that if the input x and y are integers, then the calculated x′ and y′ must also be integers, and the inverse transformation is:

Formula (2) is the integer lifting transformation of formula (1), and formula (3) is the inverse integer lifting transformation of formula (1). In addition, the cascade of integer lifting transformations can also achieve reversible integer-to-integer transformations.

Lifting transformations over finite integer fields can also implement reversible transformations from finite integer fields to finite integer fields:

Definition Transforms are the single and full maps of the discrete point field {(x,y):0≤x<M,0≤y<N} to itself. For formula (1), when 0≤x<M, 0≤y<N, the lifting transformation on the corresponding finite integer field can be constructed as follows:

The corresponding inverse transformation is:

Likewise, the concatenation of lifting transformations over finite integer fields can also implement reversible transformations from finite integer fields to finite integer fields.

However, the space limitation of GIS vector data and the integer transformation requirements of point and line serial numbers are basically consistent with the characteristics of integer lifting transformation on finite fields, so this transformation method can be well applied to vector data scrambling. However, the line-surface layer of GIS vector data is composed of line elements with different numbers of point elements, which belongs to an unsaturated matrix and does not fully meet the requirements of finite fields. Therefore, in order to facilitate the transformation of data organization and improve the efficiency of data processing, the vector data can be "supplemented" into a "square matrix" form to construct a finite field scrambling transformation space, and then realize the global scrambling between GIS vector data feature classes and elements .

Contents of the invention

The object of the present invention is: based on the principle of preferentially destroying the topological relationship between elements, the quasi-affine transformation method on the finite integer domain and the characteristics of GIS vector data, a kind of scrambling and restoration method for line-surface type GIS vector data is proposed, thereby Provide technical support for the safe transmission, packaging and storage of GIS vector data.

In order to achieve the above object, the technical scheme that the present invention takes is:

A method for scrambling and restoring a GIS vector data line surface layer, comprising the following steps:

(1) Shuffle process

Step 11: Construct vector data finite field scrambling transformation space

a) Open a line-surface type GIS vector data file, and read the spatial data of each element in turn, as well as the total number I of line-surface elements and the number J of point elements of the line-surface with the largest number of points;

b) Construct the vector data finite field space, and determine the discrete point field {(x,y):0≤x<I,0≤y<J} of the scrambling transformation, where x is the serial number of the line and surface elements of the vector data, and y is The serial number of the point element;

Step 12: Determine the scrambling transformation rules

The general form of an affine transformation is

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; ax</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; by</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; e</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; cx</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; dy</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; f</span>}\end{array}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\right.$

When the coefficient satisfies $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|=1,$ When c≠0, formula (1) can be simplified as:

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

This transformation is limited to the discrete point domain {(x,y):0≤x<I,0≤y<J}, and the translation parameters e and f are integrated into the last integer lifting transformation for simple rounding and rounding, and other Part of it is realized by integer lifting transformation, which can realize the quasi-affine transformation of formula (1) on the finite integer field. The last integer lifting transformation is as follows:

Its corresponding inverse transform is:

in, Indicates the rounding and rounding operation, and mod represents the remainder operation. The non-linear rounding operation is introduced in the integer promotion transformation at all levels, so that the final result is no longer the affine transformation in the traditional sense. The integer quasi-affine transformation of this kind The inverse transformation must exist, and it is a one-to-one transformation on the finite integer field;

Step 13: Transform parameter generation

According to the formula (2), it is necessary to generate the parameters a ₁ , a ₂ , a ₃ of the integer lifting transformation, and the translation parameters e, f; using the chaotic system , input the key file to iteratively generate x _n ; take intervals for x _n to get the number of iterations n ₁ , n ₂ , n ₃ , n _e , n _f of the Logistic chaotic system; iterate n ₁ , n f for the Logistic chaotic system respectively n ₂ , n ₃ , n _e , n _f times, the parameters a ₁ , a ₂ , a ₃ and translation parameters e, f of the integer lifting transformation can be obtained;

Step 14: Global scrambling

a) According to the transformation parameters in step 13, the scrambling transformation rules in step 12 and the formula (5), perform quasi-affine transformation of point element serial numbers point by point;

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)\left(\mathrm{<span\; class="notranslate">\; mod</span>}\begin{array}{c}\mathrm{<span\; class="notranslate">\; I</span>}\\ \mathrm{<span\; class="notranslate">\; J</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

b) Move the point elements at (x, y) point by point to (x′, y′) after quasi-affine transformation, that is, all the spatial data of point elements at (x, y) are assigned to (x′, y′) at the point element;

Step 15: Remove virtual points and form scrambled vector data RE

After the sequence number scrambling of point elements, point elements are organized according to the sequence numbers of line and area elements, and real points are added to the corresponding line and area elements one by one; if a virtual point is encountered, record the real point sequence number of the subsequent solid point Attribute z, to ensure that the number of vector data point elements after scrambling remains unchanged, so as to form the line-surface layer data R ^E after scrambling;

Step 16: Write the data after point-by-point scrambling into the vector data ^RE to form a scrambled data file;

(2) Restoration process

Step 21: Revert Transform Parameter Generation

According to the method of step 13 in the above process (1), input the key file, and generate the parameters a1, a2, a3 and translation parameters e, f of variable-reduction transformation;

Step 22: Global Descrambling

a) According to the restoration parameters and inverse transformation rules, the inverse transformation of the quasi-affine transformation is performed point by point; at the same time, it is necessary to judge whether the z value of the point element attribute is 0; if it is 0, the point element serial number y′ participates in the inverse operation ;Otherwise z value replaces y' to participate in the inverse operation;

b) All the spatial data of the point elements at (x′,y′) are assigned to the point elements at (x, y);

Step 23: After the inverse transformation, organize the point elements according to the serial numbers of the line-area elements, and add the point elements to the corresponding line-area elements one by one to form and display the scrambled line-area layer data ^RD .

Based on the principle of preferentially destroying the topological relationship between elements, the quasi-affine transformation method on the finite integer field and the characteristics of GIS vector data, the present invention performs scrambling and restoration of line-surface elements for line-surface type GIS vector data. The method has the advantages of Randomness, reversibility and other characteristics can provide effective technical means for the safe transmission, packaging and storage of geospatial data.

Description of drawings

Fig. 1 is a flow chart of data scrambling in the method of the present invention;

Fig. 2 is a flow chart of data restoration in the method of the present invention;

Fig. 3 is a schematic diagram of processing virtual points under finite fields in the method of the present invention;

Fig. 4 is the experimental data that the embodiment of the present invention adopts;

Fig. 5 is a scrambling effect diagram of vector data in an embodiment of the present invention;

Fig. 6 is an effect diagram of restoring scrambled vector data in the embodiment of the present invention.

detailed description

Further details will be given below in conjunction with the accompanying drawings and embodiments.

In this embodiment, a typical shp line layer data R is selected, and the whole process of generating transformation parameters, scrambling and restoring vector data (the same method can be used for surface layer data) is further described in detail. In this embodiment, the vector data in shp format is selected as the 1:4 million provincial boundary layer of China (as shown in FIG. 4 ) as the experimental data.

(1) Scrambling process for line layer data

Step 11: Construct a finite field scrambling transformation space

a) Open the shp line layer data, and sequentially read the information of point elements contained in each line element in the line layer data. In this embodiment, the total number I of line elements is 1785, and the line point elements containing the most points The number J is 500;

b) Construct the vector data finite field space, and determine the discrete point field {(x,y):0≤x<1785,0≤y<500} of the scrambling transformation, where x is the serial number of the vector data line element, and y is the point The ordinal number of the element.

Step 12: Determine the scrambling transformation rules

The general form of an affine transformation is

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; ax</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; by</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; e</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; cx</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; dy</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; f</span>}\end{array}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\right.$

in $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|\&NotEqual;0,$ Write it in matrix form:

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; a</span>}& \mathrm{<span\; class="notranslate">\; b</span>}\\ \mathrm{<span\; class="notranslate">\; c</span>}& \mathrm{<span\; class="notranslate">\; d</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

For the general affine transformation defined by formula (1), when the coefficient satisfies $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|=1,$ When c≠0, formula (1) can be decomposed as follows:

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; a</span>}& \mathrm{<span\; class="notranslate">\; b</span>}\\ \mathrm{<span\; class="notranslate">\; c</span>}& \mathrm{<span\; class="notranslate">\; d</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \frac{\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; c</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; c</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; a</span>}}{\mathrm{<span\; class="notranslate">\; c</span>}}\mathrm{<span\; class="notranslate">\; d</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; ad</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; bc</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

It can be simplified as:

$\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

This transformation is limited to the discrete point domain {(x,y):0≤x<I,0≤y<J}, and the translation parameters e and f are integrated into the last integer lifting transformation for simple rounding and rounding, and other Part of it is realized by integer lifting transformation, which can realize the quasi-affine transformation of formula (1) on the finite integer field. The final integer promotion transformation is as follows:

Its corresponding inverse transform is:

in, Indicates rounding and rounding operations, and mod represents remainder operations. Non-linear rounding operations are introduced in integer promotion transformations at all levels, so that the final result is no longer an affine transformation in the traditional sense. The inverse transformation of this integer quasi-affine transformation must exist, and it is a one-to-one transformation on the finite integer field.

Step 13: Generate Transform Parameters

Enter the key file, use the chaos system Generate x _n iteratively; take intervals for x _n to get the iteration times n ₁ , n ₂ , n ₃ , n _e , n _f of the Logistic chaotic system; iterate n ₁ , n ₂ , n ₃ respectively for the Logistic chaotic system , n _e , n _f times, positioning and enlarging the values to obtain the parameters a ₁ =0.13, a ₂ =0.47, a ₃ =0.88 of the integer lifting transformation, and the translation parameters e=10.26, f=5.65.

The randomness of these five transformation parameters greatly facilitates the selection of keys and increases the security of the system, and the selection of parameters determines the degree of data scrambling to a certain extent.

Step 14: Global scrambling

a) The transformation is limited to the discrete point domain {(x,y):0≤x<1785,0≤y<500}, and the translation parameters e, f are integrated into the last integer lifting transformation for simple rounding , and other parts are realized by integer promotion transformation, the specific transformation process is as follows:

So the transformation formula is as follows:

b) Substituting the transformation parameters, performing the quasi-affine transformation of the point element serial number point by point, and assigning all the spatial data of the original point element at (x, y) to the point element at (x′,y′).

For example, the first point element of the first line, that is, the point element at (0,0), is quasi-affine transformed to (11,6) through the above transformation formula, that is, the seventh point of the 12th line, That is to assign all the spatial information of the point feature at (0,0) to the point feature at (11,6).

Step 15: Remove virtual points and form scrambled vector data R ^E

After the scrambling transformation by the above method, the point elements are organized according to the serial numbers of the line elements, and the real points are added to the corresponding line elements one by one. Since the number of point elements contained in each line element is inconsistent and belongs to an unsaturated matrix, the number of point elements of the transformed line element is uncertain, and a virtual point will appear before the real point, as shown in Figure 3. If (0 , The real point at 4) is transformed into the real point at (4, 7), but there is no point at (4, 4) (4, 5) (4, 6), which is a virtual point. In order to ensure that the number of vector data point elements after scrambling remains unchanged, it is necessary to remove the virtual points, and record the real point numbers of the real points after the virtual points into the attribute z. If after the scrambling transformation, the first 69 point elements of the first line element are all virtual points, the virtual points need to be removed and the real point numbers of the real points after the virtual points should be recorded in the attribute z. At this time, the first real point The serial number of is (0, 0), and its z-value is 69. According to this method, the real points are read into the corresponding line elements one by one to form the scrambled vector data R ^E . The point element at (0,4) in the figure is scrambled and transformed to the serial number (4,3), and its attribute z value is 7.

Step 16: After point-by-point processing is completed, scrambled vector data ^RE is formed.

(2) Restoration process for line layer data

Step 21: Revert Transform Parameter Generation

According to the method of step 13 in the above process (1), input the key file, and generate the parameters a ₁ , a ₂ , a ₃ and the translation parameters e, f of the variable reduction transformation.

Step 22: Global Descrambling

a) The concatenation of the lifting transformation on the finite integer field can realize the reversible transformation from the finite integer field to the finite integer field. The specific inverse transformation process is as follows:

make $\left(\begin{array}{c}{x}^{\&prime;}\\ {\mathrm{the\; y}}^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ \mathrm{the\; y}\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)\left(\mathrm{mod}\begin{array}{c}I\\ J\end{array}\right)=\left(\begin{array}{c}p\\ q\end{array}\right)\left(\begin{array}{c}e\\ f\end{array}\right)\left({\mathrm{mod}}_J^I\right)(p\&Greater\; Equal;0,q\&Greater\; Equal;0)$

but

so,

b) Substituting the restoration parameters and performing the inverse transformation of the serial numbers of point elements point by point. At the same time, in the inverse transformation, it is first necessary to determine whether the z value of the point element attribute is 0. If it is 0, then y' participates in the inverse operation; otherwise z value replaces y' in the inverse operation. After the inverse transformation, the spatial information and attribute values of the point elements at (x′, y′) are assigned to the point elements at (x, y).

Step 23: After the inverse transformation, organize the point elements according to the serial numbers of the line elements, and add the point elements to the corresponding line elements one by one to form the scrambled shp line-surface layer data R ^D .

(3) Experimental analysis

It can be seen from the above embodiments (Figs. 4, 5, 6) that the present invention is based on the principle of preferentially destroying the topological relationship between elements, the quasi-affine transformation method on the finite integer field and the characteristics of GIS vector data, aiming at shp line layer data, Scrambling and restoration of line elements. In the present invention, its restoration transformation has a concise analytical expression, which can be restored without iteration of the number of cycles, and the data after the scrambling process has the same or similar organizational structure and data format as the original data, thus having higher processing efficiency. Efficiency and better security can effectively guarantee the security of geospatial data in data transmission, packaging and storage.

In the embodiment of the present invention, only the line layer data in shp format is used for scrambling and restoration processing, while the surface element can be regarded as a closed line. This method is also applicable to surface layer data; it is also applicable to GML, E00, MIF Scrambling and restoration processing of GIS vector data in other formats.

Claims (1)

1. a kind of scrambling and restoration method of GIS vector data line surface layer, it is characterized in that, comprises the steps: (1) Shuffle process Step 11: Construct vector data finite field scrambling transformation space a) Open a line-surface type GIS vector data file, read the spatial data of each element in turn, and the total number I of line-surface elements and the point element number J of the line-surface element containing the largest number of points; b) Construct the vector data finite field space, and determine the discrete point field {(x, y): 0≤x<I, 0≤y<J} of the scrambling transformation, where x is the serial number of the line and surface elements of the vector data, and y is The serial number of the point element; Step 12: Determine the scrambling transformation rules The general form of an affine transformation is $\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; e</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$ When the coefficient satisfies When c≠0, formula (1) can be simplified as: $\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$ This transformation is limited to the discrete point field {(x,y): 0≤x<I, 0≤y<J}, and the transformation parameters a ₁ , a ₂ , a ₃ are brought in respectively to realize integer lifting transformation at all levels. The translation parameters e and f are integrated into the last integer lifting transformation for simple rounding, and the quasi-affine transformation of formula (1) on the finite integer field can be realized. The last integer lifting transformation is as follows: Its corresponding inverse transform is: in, Indicates the rounding and rounding operation, and mod represents the remainder operation. The non-linear rounding operation is introduced in the integer promotion transformation at all levels, so that the final result is no longer the affine transformation in the traditional sense. The integer quasi-affine transformation of this kind The inverse transformation must exist, and it is a one-to-one transformation on the finite integer field; Step 13: Transform parameter generation According to the formula (2), the parameters a ₁ , a ₂ , a ₃ and the translation parameters e, f of the integer lifting transformation need to be generated; using the chaotic system Input the key file to iteratively generate x _n ; take intervals for x _n to get the number of iterations n ₁ , n ₂ , n ₃ , n _e , n _f of the Logistic chaotic system; iterate n ₁ , n respectively for the Logistic chaotic system ₂ , n ₃ , n _e , n _f times, the parameters a ₁ , a ₂ , a ₃ and translation parameters e, f of the integer lifting transformation can be obtained; Step 14: Global scrambling a) according to the transformation parameters in step 13, the scrambling transformation rules and formula (5) in step 12, carry out the quasi-affine transformation of point element sequence number point by point; $\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; \&prime;</span>}\end{array}\right)<span\; class="notranslate">\; =</span>\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right)\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; x</span>}\\ \mathrm{<span\; class="notranslate">\; the\; y</span>}\end{array}\right)<span\; class="notranslate">\; +</span>\left(\begin{array}{c}\mathrm{<span\; class="notranslate">\; e</span>}\\ \mathrm{<span\; class="notranslate">\; f</span>}\end{array}\right)<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; mod</span>}\begin{array}{c}\mathrm{<span\; class="notranslate">\; I</span>}\\ \mathrm{<span\; class="notranslate">\; J</span>}\end{array}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$ b) Move the point elements at (x, y) point by point to (x′, y′) after quasi-affine transformation, that is, all the spatial data of point elements at (x, y) are assigned to (x′, y′) at the point element; Step 15: Remove virtual points and form scrambled vector data R ^E After the sequence number scrambling of point elements, point elements are organized according to the sequence numbers of line and area elements, and real points are added to the corresponding line and area elements one by one; if a virtual point is encountered, record the real point sequence number of the subsequent solid point Attribute z, to ensure that the number of vector data point elements after scrambling remains unchanged, so as to form the line-surface layer data R ^E after scrambling; (2) Restoration process Step 21: Revert Transform Parameter Generation According to the method of step 13 in the above-mentioned process (1), the key file is input, and the parameters a ₁ , a ₂ , a ₃ and translation parameters e, f of the restoration transformation are generated; Step 22: Global Descrambling a) According to the restoration parameters and inverse transformation rules, the inverse transformation of the quasi-affine transformation is performed point by point; at the same time, it is necessary to judge whether the z value of the point element attribute is 0; if it is 0, the point element serial number y′ participates in the inverse operation ;Otherwise z value replaces y' to participate in the inverse operation; b) Assign all the spatial data of the point elements at (x', y') to the point elements at (x, y); Step 23: After the inverse transformation, organize the point elements according to the serial numbers of the line-area elements, and add the point elements to the corresponding line-area elements one by one to form and display the scrambled line-area layer data ^RD .